{"title":"人工智能在光伏领域终结了吗?来自中国的证据","authors":"Haoran Zhang , Xiaohong Yu , Zixuan Gao","doi":"10.1016/j.eneco.2025.108423","DOIUrl":null,"url":null,"abstract":"<div><div>The purpose of this paper is to explore the intersection of AI and PV in the energy sector, and to analyze in depth this profound change in the energy industry brought about by the combination of Photovoltaic and AI. This study employs a full-sample and sub-sample approach to determine the interrelationship between China's Artificial Intelligence Index (AI) and Photovoltaic Index (PI). The quantitative discussion shows that AI has both favorable and unfavorable impacts on PI, and the positive impacts suggest that AI plays a motivating role in PV and contributes to the operational efficiency and economic benefits of PV plants. However, if the impact of AI on PI is negative, this incentivizing role cannot always be determined, mainly due to existing bottlenecks in PV technology. At the same time, PI has both favorable and unfavorable impacts on AI, and the positive impacts of PI on AI highlight the enormous potential and opportunities offered by the convergence of PV + AI. In terms of AI power support, PV power generation does show unrivaled potential. However, the negative impacts of PI on AI also imply the risks and challenges that may be posed by data security and privacy protection issues, transparency and interpretability issues of AI algorithms, and so on. This study provides a fresh perspective on the future development of energy-technology convergence and will provide meaningful recommendations to promote AI technology and PV industry to enhance each other for win-win situation.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"145 ","pages":"Article 108423"},"PeriodicalIF":14.2000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Is the end of AI in photovoltaic power? Evidence from China\",\"authors\":\"Haoran Zhang , Xiaohong Yu , Zixuan Gao\",\"doi\":\"10.1016/j.eneco.2025.108423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The purpose of this paper is to explore the intersection of AI and PV in the energy sector, and to analyze in depth this profound change in the energy industry brought about by the combination of Photovoltaic and AI. This study employs a full-sample and sub-sample approach to determine the interrelationship between China's Artificial Intelligence Index (AI) and Photovoltaic Index (PI). The quantitative discussion shows that AI has both favorable and unfavorable impacts on PI, and the positive impacts suggest that AI plays a motivating role in PV and contributes to the operational efficiency and economic benefits of PV plants. However, if the impact of AI on PI is negative, this incentivizing role cannot always be determined, mainly due to existing bottlenecks in PV technology. At the same time, PI has both favorable and unfavorable impacts on AI, and the positive impacts of PI on AI highlight the enormous potential and opportunities offered by the convergence of PV + AI. In terms of AI power support, PV power generation does show unrivaled potential. However, the negative impacts of PI on AI also imply the risks and challenges that may be posed by data security and privacy protection issues, transparency and interpretability issues of AI algorithms, and so on. This study provides a fresh perspective on the future development of energy-technology convergence and will provide meaningful recommendations to promote AI technology and PV industry to enhance each other for win-win situation.</div></div>\",\"PeriodicalId\":11665,\"journal\":{\"name\":\"Energy Economics\",\"volume\":\"145 \",\"pages\":\"Article 108423\"},\"PeriodicalIF\":14.2000,\"publicationDate\":\"2025-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0140988325002476\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0140988325002476","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Is the end of AI in photovoltaic power? Evidence from China
The purpose of this paper is to explore the intersection of AI and PV in the energy sector, and to analyze in depth this profound change in the energy industry brought about by the combination of Photovoltaic and AI. This study employs a full-sample and sub-sample approach to determine the interrelationship between China's Artificial Intelligence Index (AI) and Photovoltaic Index (PI). The quantitative discussion shows that AI has both favorable and unfavorable impacts on PI, and the positive impacts suggest that AI plays a motivating role in PV and contributes to the operational efficiency and economic benefits of PV plants. However, if the impact of AI on PI is negative, this incentivizing role cannot always be determined, mainly due to existing bottlenecks in PV technology. At the same time, PI has both favorable and unfavorable impacts on AI, and the positive impacts of PI on AI highlight the enormous potential and opportunities offered by the convergence of PV + AI. In terms of AI power support, PV power generation does show unrivaled potential. However, the negative impacts of PI on AI also imply the risks and challenges that may be posed by data security and privacy protection issues, transparency and interpretability issues of AI algorithms, and so on. This study provides a fresh perspective on the future development of energy-technology convergence and will provide meaningful recommendations to promote AI technology and PV industry to enhance each other for win-win situation.
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.